1. Field of the Art
The disclosure relates generally to communication systems, and more specifically, to forward error correction codes.
2. Description of the Related Art
Error correction is important component of applications such as optical transport networks and magnetic recording devices. For example, in the next generation of coherent optical communication systems, powerful forward error correction (FEC) codes are desirable to achieve high net effective coding gain (NECG) (e.g., ≥10 dB at a bit error rate (BER) of 10−15). Given their performance and suitability for parallel processing, large block size low density parity check (LDPC) codes are a promising solution for ultra-high speed optical fiber communication systems. Because of the large block size to achieve high NECG, the use of low complexity soft decoding techniques such as the min-sum algorithm (MSA) is often used when aiming at an efficient very large scale integration (VLSI) implementation. The main stumbling block for the application of this coding approach has been the fact that traditional LDPC codes suffer from BER error floors that are undesirably high.
The error floor is a phenomenon encountered in traditional implementations of iterated sparse graph-based error correcting codes like LDPC codes and Turbo Codes (TC). When the bit error ratio (BER) curve is plotted for conventional codes like Reed Solomon codes under algebraic decoding or for convolutional codes under Viterbi decoding, the curve steadily decreases as the Signal to Noise Ratio (SNR) condition becomes better. For LDPC codes and TC, however, there is a point after which the curve does not fall as quickly as before. In other words, there is a region in which performance flattens. This region is called the error floor region.
To reduce these error floors, some decoders concatenate an LDPC code with a hard-decision-based block code. However, this approach increases the overhead and reduces the performance and the spectral efficiency.